I-Corps: Bio-Inspired Predictive Engineering Analysis Tool

I-Corps：仿生预测工程分析工具

• 批准号: 1737815
• 负责人: Devinder Kaur
• 金额: $ 5万
• 依托单位: University of Toledo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737815&HistoricalAwards=false
• 关键词: Corps; Bio; Inspired; Predictive; Engineering

The broader impact/commercial potential of this I-Corps project is to obtain the benefits available from modernizing legacy processes in the made-to-order design manufacturing industry. Traditionally the mathematical processes used to analyze potential designs are very linear in nature, and do not offer the manufacturer a complete picture of the overall impacts of the non-linear parts of their designs. With the predictive engineering analysis tool developed here, a manufacturing facility can preview the results available from using a particular engineering design prior to the actual manufacturing and testing of the physical parts. Design parameters and environmental conditions can also be inserted into the tool which are then used to better predict the behavior of the part after it is produced. This innovative virtual tool has the potential to be added to the set of existing design and testing tools already being used and let manufacturers predict the success or failure of a part. The impact of this tool would be decreased time to market, eliminating the guesswork now used in certain aspects of a design and saving valuable physical resources.This I-Corps project defines an innovative scalable software tool that is capable of virtually predicting the success or failure of an engineering design prior to production. The technique is based on the mathematical modeling of the coordinated behaviors of biological system. This allows the tool to quickly search and intelligently predict the best solution sets to a multi-objective problem in a given design space. This project employs these innovative bio-inspired techniques to develop algorithms which are applied to engineering designs to produce an ideal set of solutions based on user defined objectives. Bio-inspired algorithms have been shown to improve upon current standard rigid mathematical techniques. This project provides the flexibility to implement an approach that is able to search the entire problem space at once therefore giving better visibility to all of the possible solutions. Since no particular parameter in isolation impacts the outcome of the algorithm, the user is presented with the opportunity to shift the input parameters and rerun the optimization. Further this I-Corps project attempts to explore and define the input parameters for a variety of industries, and assist the end user in coming up with better designs for their products.

这个I-Corps项目的更广泛的影响/商业潜力是从定制设计制造业的传统流程现代化中获得好处。传统上，用于分析潜在设计的数学过程本质上是非常线性的，并且不能为制造商提供其设计的非线性部分的整体影响的完整画面。借助此处开发的预测性工程分析工具，制造设施可以在实际制造和测试物理部件之前预览使用特定工程设计的可用结果。设计参数和环境条件也可以插入到工具中，然后用于更好地预测零件在生产后的行为。这种创新的虚拟工具有可能被添加到现有的设计和测试工具中，让制造商预测零件的成功或失败。这个工具的影响将是缩短上市时间，消除猜测现在使用的设计的某些方面，节省宝贵的物理resources.This I-Corps项目定义了一个创新的可扩展的软件工具，能够虚拟预测生产前的工程设计的成功或失败。该技术基于生物系统协调行为的数学建模。这允许该工具快速搜索并智能预测给定设计空间中多目标问题的最佳解决方案集。该项目采用这些创新的生物启发技术开发算法，应用于工程设计，以根据用户定义的目标产生一套理想的解决方案。生物启发算法已经被证明可以改进当前标准的严格数学技术。该项目提供了灵活性，可以实现一种能够立即搜索整个问题空间的方法，从而更好地了解所有可能的解决方案。由于没有特定的参数孤立地影响算法的结果，因此用户有机会改变输入参数并重新优化。 此外，这个I-Corps项目试图探索和定义各种行业的输入参数，并帮助最终用户为他们的产品提出更好的设计。